San Francisco, California
Infrastructure for teaching AI taste and judgment
Taste Labs builds data, infrastructure, and evaluation systems that help AI models and agents develop taste, judgment, and design quality. It serves AI labs and teams building creative or subjective-domain applications by making qualities such as visual style, writing, and design measurable and trainable.
Sources, screens, and onboards creative and technical freelance talent across US and LATAM markets. The role requires 3–6+ years of recruiting or talent operations experience, strong organization, creative-community fluency, and technical understanding of design and frontend disciplines.
Senior generalist designer shaping Taste’s web product, creative AI tooling, brand, and marketing surfaces. The role requires 6+ years of experience, strong product design execution, visual taste, prototyping ability, and close collaboration with engineers.
Build and evaluate post-trained machine learning models for subjective domains such as design and writing. The role owns experiments, reward models, judges, infrastructure, data and evaluation pipelines, and research publications while collaborating with AI labs.
The Growth Lead will grow and productize a TasteMakers community by optimizing acquisition, engagement, retention, messaging, analytics, SEO, and paid growth. The role requires startup experience, strong analytical ability, and comfort building systems, dashboards, and growth experiments.
This role investigates and operationalizes what makes design excellent, translating design judgment into measurable evaluations, interfaces, and AI products. It suits a highly opinionated designer with strong research instincts, hands-on AI and coding experience, and broad cross-functional collaboration skills.
Build AI systems for taste evaluation, synthetic data, agent tooling, retrieval, crawling, inference, and user-facing experiences. The role favors hands-on experience shipping LLM and agent systems, early-stage startup experience, and comfort inventing infrastructure in ambiguous domains.
Runs the operating system for a curated expert network, maintaining supply data, onboarding workflows, funnel reporting, reactivation campaigns, and engagement touchpoints. The role suits an independent operator comfortable building systems amid ambiguity and prioritizing quality over volume.
Leads end-to-end data development projects connecting frontier-lab researchers, expert contributors, and engineering teams. The role combines product operations, strategy, project ownership, quality management, and process optimization in an AI-focused environment.
Build AI systems, agent harnesses, evaluation pipelines, retrieval infrastructure, crawling systems, and inference APIs that make subjective design quality measurable. The role requires experience building AI-forward products or systems, strong technical judgment, and comfort solving ambiguous startup problems.